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长春光学精密机械与物... [2]
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会议论文 [2]
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2011 [1]
2010 [1]
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Adaptive Wiener filtering with Gaussian fitted point spread function in image restoration (EI CONFERENCE)
会议论文
2011 IEEE 2nd International Conference on Software Engineering and Service Science, ICSESS 2011, July 15, 2011 - July 17, 2011, Beijing, China
Yang L.
;
Zhang X.
;
Ren J.
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浏览/下载:30/0
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提交时间:2013/03/25
In the imaging process of the space remote sensing camera
there was degradation phenomenon in the acquired images. In order to reduce the image blur caused by the degradation
the remote sensing images were restored to give prominence to the characteristic objects in the images. First
the frequency-domain notch filter was adopted to remove strip noises in the images. Then using the ground characters with the knife-edge shape in the images
the point spread function of the imaging system was estimated. In order to improve the accuracy
the estimated point spread function was corrected with Gaussian fitting method. Finally
the images were restored using the adaptive Wiener filtering with the fitted point spread function. Experimental results of the real remote sensing images showed that almost all strip noises in the images were eliminated. After the denoised images were restored
its variance and its gray mean gradient increased
also its laplacian gradient increased. Restoration with Gaussian fitted point spread function is beneficial to interpreting and analyzing the remote sensing images. After restoration
the blur phenomenon of the images is reduced. The characters are highlighted
and the visual effect of the images is clearer. 2011 IEEE.
Remote sensing image restoration using estimated point spread function (EI CONFERENCE)
会议论文
2010 International Conference on Information, Networking and Automation, ICINA 2010, October 17, 2010 - October 19, 2010, Kunming, China
Yang L.
;
Ren J.
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浏览/下载:27/0
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提交时间:2013/03/25
In order to reduce image blur caused by the degradation phenomenon in the imaging process
the acquired images of the space remote sensing camera are restored. First
the frequency-domain notch filter is adopted to remove strip noises in the images. Then degradation function
which is referred to as the point spread function (PSF) of the imaging system is estimated using the knife-edge method. To improve the accuracy of the estimation
the estimated PSF is adjusted with Gaussian fitting. Finally
the images are restored by Wiener filtering with the fitted PSF. The restoration results of the remote sensing images show that almost all strip noises are eliminated by the notch filter. After denoising and restoration
the variance of the remote sensing image worked with in this paper increases 30.979 and the gray mean gradient increases 3.312. Due to Gaussian fitting
the accuracy of the PSF estimation is heightened. Image restoration with the final PSF is benefit to interpreting and analyzing the remote sensing images. After restoration
the contrasts of the restored images are increased and the visual effects become clearer. 2010 IEEE.
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